linolevan

Encoder I’m working on as a side project, not publicly released (but feel free to pull the included files to prove it to yourself)

I'll post it to bsky/HN at some point in the future!

It's just a side project I'm working on with some friends. May release it if it's interesting to folks.

39.2% (!!!) of people get diagnosed with cancer at some point in their lives

What is hard about migrating between password managers? At least on MacOS you can just open passwords and export all to another app?

While it is definitely true that original power drops were due to lower lumens, few things:

- reflective housing is super inefficient (~70% losses on the bounced light off typical material, at the top end expensive stuff still ~23%), still better than just losing the light upwards but not as many lumens on the road as a lab test would show

- Today LEDs are more efficient than sodium

Some math: 100W HPS cobra head lamp prdouces 9.5k lumens, including ballast it draws ~133W from the wall. Lab test shows about 70% of the lamp's light leaves the fixture (with the rest being lost in the housing) leading to ~7k lumens exiting. Roughly 53 lm/W.

LED cobra head lamps get like ~125 lm/W on the low end + fade much more slowly than sodium

I’m very skeptical of these results. I run a pretty large group paper website on top of arXiv and we run pangram on papers. The numbers are not nearly this high.

One thing I see a lot is papers flagged as AI because they include llm rollouts in the paper as examples.

Neat optimization, I've never seen that before. Thanks for sharing.

Can we note that this is a 2024 paper in the title?